Whole blood transcriptome analysis using RNA sequencing in individuals with insomnia disorder and good sleepers : a pilot study
Copyright © 2021 The Author(s). Published by Elsevier B.V. All rights reserved..
BACKGROUND: Insomnia is a highly prevalent condition that is associated with negative health outcomes, yet little is known about the underlying molecular mechanisms.
METHOD: RNA sequencing was conducted using blood samples from 15 individuals with primary insomnia and 15 age- and gender-matched good sleeper controls. The RNA library was sequenced with 150 base pair paired-ends on the Illumina NovaSeq-6000 platform. Alignment was performed using human reference genome hg38. Differential gene expression analysis was performed using DESeq2 following alignment, using log fold change ±0.50, and had a false discovery rate p-value <0.05. Pathway analysis was performed using Ingenuity Pathway Analysis.
RESULTS: We found 288 differentially expressed genes in insomnia patients when compared to controls. Upregulated genes included LINC02224 (Long Intergenic Non-Protein Coding RNA 2224), DUX4L9 (Double Homeobox 4 Like 9), and TUSC3 (Tumor Suppressor Candidate 3) and down regulated genes included CTXN2 (Cortexin 2), CSMD1 (CUB And Sushi Multiple Domains 1), and SLC12A1 (Solute Carrier Family 12 Member 1). Ingenuity® Pathway Analysis (IPA) revealed 3 associated networks (score>40) with genes and hubs related to inflammation (nuclear factor-kB), oxidative stress (Mitochondrial complex 1) and ubiquitination.
CONCLUSION: Differentially expressed genes in this analysis are functionally associated with inflammation and immune response, mitochondrial and metabolic processes. Further research into the transcriptomic changes in insomnia is needed to understand related pathways to the disorder and provide new avenues for diagnostics and therapeutics.
Medienart: |
E-Artikel |
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Erscheinungsjahr: |
2021 |
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Erschienen: |
2021 |
Enthalten in: |
Zur Gesamtaufnahme - volume:80 |
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Enthalten in: |
Sleep medicine - 80(2021) vom: 21. Apr., Seite 1-8 |
Sprache: |
Englisch |
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Beteiligte Personen: |
Mithani, Sara [VerfasserIn] |
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Links: |
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Themen: |
Bioinformatics |
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Anmerkungen: |
Date Completed 05.07.2021 Date Revised 05.07.2021 published: Print-Electronic Citation Status MEDLINE |
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doi: |
10.1016/j.sleep.2021.01.013 |
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funding: |
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Förderinstitution / Projekttitel: |
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PPN (Katalog-ID): |
NLM320909239 |
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520 | |a Copyright © 2021 The Author(s). Published by Elsevier B.V. All rights reserved. | ||
520 | |a BACKGROUND: Insomnia is a highly prevalent condition that is associated with negative health outcomes, yet little is known about the underlying molecular mechanisms | ||
520 | |a METHOD: RNA sequencing was conducted using blood samples from 15 individuals with primary insomnia and 15 age- and gender-matched good sleeper controls. The RNA library was sequenced with 150 base pair paired-ends on the Illumina NovaSeq-6000 platform. Alignment was performed using human reference genome hg38. Differential gene expression analysis was performed using DESeq2 following alignment, using log fold change ±0.50, and had a false discovery rate p-value <0.05. Pathway analysis was performed using Ingenuity Pathway Analysis | ||
520 | |a RESULTS: We found 288 differentially expressed genes in insomnia patients when compared to controls. Upregulated genes included LINC02224 (Long Intergenic Non-Protein Coding RNA 2224), DUX4L9 (Double Homeobox 4 Like 9), and TUSC3 (Tumor Suppressor Candidate 3) and down regulated genes included CTXN2 (Cortexin 2), CSMD1 (CUB And Sushi Multiple Domains 1), and SLC12A1 (Solute Carrier Family 12 Member 1). Ingenuity® Pathway Analysis (IPA) revealed 3 associated networks (score>40) with genes and hubs related to inflammation (nuclear factor-kB), oxidative stress (Mitochondrial complex 1) and ubiquitination | ||
520 | |a CONCLUSION: Differentially expressed genes in this analysis are functionally associated with inflammation and immune response, mitochondrial and metabolic processes. Further research into the transcriptomic changes in insomnia is needed to understand related pathways to the disorder and provide new avenues for diagnostics and therapeutics | ||
650 | 4 | |a Journal Article | |
650 | 4 | |a Research Support, Non-U.S. Gov't | |
650 | 4 | |a Bioinformatics | |
650 | 4 | |a IPA | |
650 | 4 | |a Inflammation | |
650 | 4 | |a Network analysis | |
650 | 4 | |a Sleep | |
700 | 1 | |a Yun, Sijung |e verfasserin |4 aut | |
700 | 1 | |a Leete, Jacqueline J |e verfasserin |4 aut | |
700 | 1 | |a Guedes, Vivian A |e verfasserin |4 aut | |
700 | 1 | |a Fink, Anne M |e verfasserin |4 aut | |
700 | 1 | |a Pattinson, Cassandra L |e verfasserin |4 aut | |
700 | 1 | |a Kim, Hyung-Suk |e verfasserin |4 aut | |
700 | 1 | |a Weljie, Aalim |e verfasserin |4 aut | |
700 | 1 | |a Gill, Jessica M |e verfasserin |4 aut | |
700 | 1 | |a Gehrman, Philip |e verfasserin |4 aut | |
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